Search results

The primary purpose of this paper is to examine how generative Artificial Intelligence (AI) such as ChatGPT may serve as a new context for management theories and concepts.

The paper presents the analyses of selected management theories on decision-making, knowledge management, customer service, human resource management and administrative tasks and explains what may change after generative AI adoption.

The paper indicates that some management theories and concepts need to be studied in the generative AI environment that may influence managerial work at the strategic, functional and administrative levels.

This paper is an opinion piece article and does not refer to empirical data. It formulates some conclusions to further empirical research studies.

The paper analyzes selected management theories in a new technological setting. The paper also provides information about the functions of generative AI that are useful in understanding and overcoming how new technology may change organizations and management.

This study investigates online corporate opinion leadership on professional social media from two different perspectives: first, how corporate opinion leadership indicated by corporate followers is related to company revenue and second, what are the drivers and mediators of corporate opinion leadership?

The authors randomly selected more than 300 companies with active profiles on LinkedIn from the S&P 500 list and then collected data on corporate followers as an indicator of corporate opinion leadership and revenue during a year. Moreover, the authors collected daily information on content generated by companies, users, and employees such as job posts, users' reactions to posts, and employee profiles during a 44-day period, which allowed the authors to apply panel estimation techniques to estimate the determinants of corporate opinion leadership.

The estimation results reveal that corporate opinion leadership and business revenue are positively and significantly correlated. Furthermore, after controlling for firm fixed effects and endogeneity, the authors show that corporate, user and employee-generated content (mediated by groups and skills) have a significant impact on corporate opinion leadership.

Individual online opinion leaders are currently paying considerable attention to practitioners. However, professional networking platforms have also created an opportunity to establish corporate opinion leaders who may play an important role in business. The study provides useful and practical insights on the activities that companies can undertake to develop corporate opinion leadership.

This study seeks to expand previous research on opinion leadership with a focus on the corporate dimension, which is increasingly visible on professional networking platforms. Contrary to former research that collected data on perceived opinion leadership, the authors obtained data directly from LinkedIn. Moreover, the authors contribute to signaling and social identity theories by exploring how professional networking platforms constitute an environment for signaling and developing multiple professional identities.

The purpose of this paper is to introduce coherent Industry 4.0 definition via a rigorous analysis framework, and provide a holistic view of technological, organizational and other key aspects (variables) of Industry 4.0 along with the identification of interdependencies that co-occur between them.

The study conducts a systematic literature review using Preferred Reporting Items for Systematic Review and Meta-Analysis methodology, and includes 675 papers analyzed both quantitatively and qualitatively. The former utilizes TIBCO Statistica. Furthermore, to define Industry 4.0, the authors reviewed 52 publications.

Industry 4.0 is a multidimensional system of value creation that includes 42 groups of terms in management, organizational and business-related variables, 30 technological and manufacturing-related variables – classified into seven categories – and several interdependencies that co-occur between them.

The analyses’ outcomes are of high importance both for academia and industry practitioners, as the findings elucidate the meaning of Industry 4.0 and may be used as the basis of future research in management, production management, industrial organizations and other Industry 4.0-related disciplines. Regarding industrial companies, the publication serves as a compendium, and should support industrial businesses in the transition from traditional manufacturing into the Industry 4.0 era.

This work’s novelty and value is threefold: first, the paper introduces an Industry 4.0 definition framework based on the most popular publications in the field. Second, the paper identifies and presents Industry 4.0’s common technologies and organizational variables via a systematic and current literature review. Finally, the paper extends the ongoing discourse on Industry 4.0. For the first time in this discipline, interdependences between identified Industry 4.0 variables are presented and discussed.

It seems that the Internet boom, which started at the end of the 1990s and finished with the spectacular collapse of the so-called dotcoms, is probably over. We are currently enjoying a period of fast and stable growth. This is manifested by the growing number of both Internet users and companies which – to an ever-increasing extent – use the Internet as a form of communication (both internal and external), promotion, sales etc. Expenditures on Internet advertising are growing continuously and now constitute more than 25% of all advertising expenditure. A natural consequence of this development is the need for the standardisation and organisation of the world of the Internet. These activities will result in a greater awareness of the benefits which this medium provides, increasing the possibilities of its use, and – most importantly – the opportunity to evaluate the return on investments made on the Internet. Nowadays, it is clear that many companies are striving to increase the quality of their activities on the Internet or to improve the effectiveness of such activities. As a consequence, the number of companies that look for indices which would enable the making of more precise and effective decisions in the scope of online operations is growing.

This chapter is dedicated to the phenomenon of the increasing role of the Internet in business, including the scale of its use by Polish and international companies. We present the most commonly used measures of marketing activities on the Internet and in social media. This group includes the indices which make it possible to determine whether a company actually needs a website. Other measures allow for the improvement in the effectiveness of the activity on the Internet, whereas others specify the costs of activities on the Internet and often serve as the basis for settlements between a company and advertising agencies or companies specialising in website design. It is worth emphasising that the Paid, Earned, Shared, Owned (PESO) model, worked out by Don Bartholomew,¹ is the basis for creation and description of indices concerning social media. This model has gained certain popularity in the social media industry. It does not, however, specify how individual indices should be named and calculated. It maps already existing indices and adapts them to specific levels of marketing communication measurement. All the measures indicated by the author of the model have been grouped into five major areas: exposure, engagement, brand awareness, action and recommendations. This model– similarly to all models of performance measurement – inspired by the sales funnel concept, adjusts certain standard indices and proposals of measurements for specific levels. Additionally, the measures are divided into four types, depending on who the owner of the content is: Paid (P) – refers to all forms of paid content; Owned (O) – all websites and web properties controlled by a company or brand; Earned (E) – the contents about a given brand created spontaneously by Internet users; and Shared (S) – the contents shared by Internet users.